Extract from webinar session on July 22. Thank you Dr Eva-Marie Muller-Stuler, Chief Data Scientist, IBM Cloud MEA for your feedback on the materials

Over a period of 3 weeks during the summer holidays, Mai Ali, instructor in Electrical Engineering at AlFaisal University in Riyadh, is leading a program to teach data science and machine learning to high school female students. The “first of a kind” program is sponsored by Mawhiba – King Abdulaziz and His Companions’ Foundation for Giftedness and Creativity. Mawhiba provides skills, training and internship opportunities to gifted students across the Kingdom of Saudi Arabia. The students are spending 35 hours a week attending lectures and labs, and solving hands-on data science and AI problems. They have already learned some Python and Matlab.

On July 22, I talked with the students. On July 29, my colleague Dr Kaoutar ElMaghraoui introduced machine learning and deep learning. On August 8, the students will participate in a hands-on workshop in Riyadh using the IBM’s Data Science Platform, led by my colleague engineer Nora AlNashwan, IBM Developer Advocate. The workshop includes:

  • Introduction to Data Science elements and techniques & the Data Science platform, including an exploration of community resources
  • Lab Session 1: Creating and deploying a machine learning model
  • Lab Session 2: Exploring and visualising data with Notebooks
  • Lab Session 3: Build a custom image classifier

We wish all the participants great success in their studies and careers – and are grateful to Mai Ali and Mawhiba for the opportunity to participate in the program.


Last Sunday July 22, I got up early to talk to the high school students in Riyadh about why it is important for them to engage in data science and AI, and the range of careers available, and the skills required. I invited two wonderful colleagues: Marie Wallace in Dublin, Ireland; and Dr Margriet Groenendijk in Bristol, UK; to join in the discussion and share their technical and career experiences. These are the slides that I shared for the session: https://developer.ibm.com/opentech/wp-content/uploads/sites/43/2018/07/WhyLearnDataScienceandMachine-Learning.SusanMalaika.20180722a.pdf The students asked many questions and participated enthusiastically in the quiz – and although some of the students spoke English, Mai took the time to translate into Arabic to ensure that the students were following along.

Marie Wallace IBM Technical Strategist & Solution Architect – @marie_wallace
Dr Margriet Groenendijk IBM Developer Advocate – @margrietgr

During Marie’s section, we discussed Marie’s career as a software architect and how she found herself listed here https://www.siliconrepublic.com/people/data-science-twitter-influencers-role-models as a key data scientist to follow. Marie explained that it was because, in addition to her work at IBM, she writes about analytics and data science, as well as delivers lectures and talks, including a Ted Talk. Marie maintains a blog here: https://allthingsanalytics.com/about/ – Marie’s latest blog entry is called “why I’m a blockchain convert“. Marie participated in the Women in Data Science conference (WiDS) in March 2018 – at the American University of Beirut – where she presented on Humanizing Analytics. Marie wrote about her WiDS experience in her blog.

During Margriet’s section, we reviewed recommender systems in particular in a commercial setting, and Margriet showed code in Github for a recommender system that she was working on for a meetup. She ran her prototype and the students enjoyed interacting with it. Recommender systerms were familiar to the students in their daily life, e.g., on-line shopping, and the impact of data science became clear to them. Another topic covered was Jupyter Notebooks that make it easy to create and share documents that contain live code, equations, visualizations and text – And I can’t wait for the JupyterCon conference in New York in August. See https://github.com/IBMCodeLondon/localcart-workshop for more information on Margriet’s example. Margriet also explained why she decided to take a Masters degree and a PhD.

This Sunday July 29, I got up early again, to mentor the call-for-code hackathon (the high school students cannot join the call-for-code initiative just yet, because the minimum age for participation is 18), and to support my colleague Dr Kaoutar ElMaghraoui who gave an excellent introduction to machine learning and deep learning.

Extract from the session by Dr Kaoutar Elmaghraoui IBM Research Scientist – @kaoutarTech – the diagram is taken from

Thank you Kaoutar, Marie, and Margriet for sharing your knowledge and skills with the students, and inspiring them – in spite of your busy schedules.

More Resources

These are videos I shared with the students – we did not have time to play them during the webinars, but I hope the students will play them in their spare time.

The top 10 uses cases for machine learning:

The next Women in Data Science (WiDS) conference is at Stanford on March 4, 2019 – and at many other locations around the world.

Women in Data Science (WiDS)

I had the good fortune to meet Mai Ali for the first time in March 2018, while participating in the Women in Data Science events in Riyadh @WiDSRiyadh. Mai invited my colleague Dr Kaoutar ElMagharoui and me to deliver a lecture at Alfaisal University a few days later. These are some of the materials I presented at that time https://developer.ibm.com/opentech/wp-content/uploads/sites/43/2018/03/IBM-Code-and-Patterns-5.malaika.pdf to students and faculty. We also participated in a career fair at the university. Our happy encounter with Mai at the excellent Women in Data Science event at KACST led to our participation in the high school program.

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